Pietro De Lellis

University Naples Federico II

Detecting salient features of network dynamical systems from time series
11:15am, Room St Clair 3B

Be it the identification of its vulnerable units or the detection of its size, uncovering the essential characteristics of a network dynamical system requires either the availability of a calibrated model or the possibility of performing tailored experiments to manipulate its topology and dynamics. However, what we typically have at our disposal is a noisy time-series of one or few of the units composing the network system. In this talk, we show that, quite surprisingly, this partial and noisy information on possibly only one unit in the system can be leveraged to identify salient features of the whole network. The scope of validity of the results and the open challenges are discussed.

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